1. Field of Application
This invention relates to receiver design in communications systems, specifically to improving the system performance in terms of the bit error rate (BER) and frame error rate (FER), and to reducing the amount of computations and/or hardware in an effective and reliable manner.
2. Description of Prior Art
Conventional Rake Receiver
A direct-sequence code division multiple access (DS-CDMA) system typically employs a rake receiver to recover information sent over a communication medium (channel), e.g., air in wireless systems. A conventional rake receiver is based upon the concept of resolvable multipaths. Multipaths are typical of wireless channels where a mobile terminal (cell phone) receives multiple copies of the signals from a base station due to reflections from the surroundings. FIG. 1 illustrates the multiple-path phenomenon in a cellular system. A mobile terminal 20 communicates with a base station 22 in a cell 24 (base cell). In FIG. 1, there are a signal path 30a directly from base station 22, a signal path 30b reflected by a building 26, and a signal 30c reflected by a mountain 28. When the delays between the multipaths are large enough, the rake receiver is able to distinguish each multipath from others, and the multipaths in such a scenario are referred to as “resolvable multipaths”. FIG. 2 illustrates a channel impulse response (CIR) seen by the rake receiver with three well-separated, or resolvable, multipaths.
A conventional rake receiver demodulates each multipath separately. In a conventional rake receiver, each multipath demodulator is referred to as a “finger”. The receiver then combines the output of each finger to obtain the demodulated data.
A conventional rake receiver has following disadvantages:                1. Intracell interference degrades the output signal-to-noise ratio (SNR) of the rake receiver. Herein the SNR refers to both the signal-to-noise ratio and the signal-to-interference-plus-noise ratio (SINR) unless stated otherwise. When the rake receiver demodulates each multipath, it treats interferences of other multipaths as noise. Such noise is referred to as intracell interference. Intracell interference cannot be suppressed by increasing the input signal strength, since the strengths of all multipaths increases proportionally to the strength of the input signal. As a result, the output SNR of the rake receiver improves much more slowly with the increasing input SNR. Eventually the output SNR is limited by an SNR ceiling. FIG. 3 illustrates such an output SNR ceiling effect. The intracell interference severely limits the BER/FER performance, and the capacity of, e.g., wireless cellular systems.        2. Each finger of the receiver requires a dedicated tracking loop. The rake receiver uses the tracking loop to track the delay (timing) and complex amplitude of the multipath assigned to a finger. The tracking loops add complexity to the rake receiver. Herein the term “complexity” denotes any measure of a receiver with respect to the amount of computations, size of the software code, memory size, circuit size, gate count, silicon area, power consumption, cost, etc.        3. It is difficult to track closely spaced multipaths. If multipaths become close to each other, the outputs of the tracking loops will contain large errors, as the multipaths are no longer well separated as in FIG. 2. The estimation errors in timing and amplitude further degrade the BER/FER performance. Sophisticated algorithms can be used to track closely spaced multipaths, see, for example, G. Fock, et al., “Channel Tracking for Rake Receivers in Closely Spaced Multipath Environments”, IEEE Journal on Selected Areas in Communications, vol. 19, no. 12, pp. 2420-2431, December 2001, incorporated by reference herein. Not only such algorithms significantly increase the complexity of the rake receiver, they also require a priori knowledge of information on delays and complex amplitudes for the multipaths to be tracked. Such information may not be available or can be hugely erroneous when estimated from closely spaced multipaths, thus degrading the performance of the tracking loops.        4. The quality of the initial multipath estimation is poor when the multipaths are closely spaced. As mentioned in previous paragraph, this has adverse effect on tracking algorithms. This also makes the finger assignment error-prone.        5. A conventional rake receiver based upon the resolvable multipath concept typically requires a sample rate that is four times (4×) the chip rate (the symbol rate of the spreading sequence) or higher, to reduce the penalty in signal-to-noise ratio (SNR) due to mis-alignment of the peak of a multipath and its corresponding sample point. Herein a sample rate which is four times the chip rate is referred to as 4× oversampling, and a sample rate which is two times the chip rate is referred to as 2× oversampling, and so on. For example, 2× oversampling results in about 0.5 dB SNR loss, while 4× oversampling reduces the SNR loss to about 0.1 dB. Higher sampling rate, however, increases the power consumption of the analog-to-digital converter (ADC) and front-end pulse-matched filter, if it is implemented digitally, which is undesirable especially in a mobile terminal that is power-limited.Generalized Rake Receiver        
A generalized rake receiver (G-rake) addresses the intracell interference problem in a conventional rake receiver. For details, see Y.-P. E. Wang, J.-F. Cheng and E. Englund, “The Benefits of Advanced Receivers for High Speed Data Communications in WCDMA”, Proceedings of IEEE Vehicular Technology Conference, pp. 132-136, September 2002, incorporated by reference herein. In short, G-rake places more fingers than there are multipaths to provide better suppression of both intracell interference and intercell interference (interference from the base stations in other cells).
A G-rake receiver has following disadvantages:                1. G-rake receiver uses the multipath decomposition of the CIR, which makes it very sensitive to channel estimation errors. Let h(t) be the composite CIR, then the multipath decomposition of h(t) can be written as        
                                          h            ⁡                          (              t              )                                =                                    ∑                              l                =                0                                            L                -                1                                      ⁢                                                  ⁢                                          a                l                            ⁢                              p                ⁡                                  (                                      t                    -                                          τ                      l                                                        )                                                                    ,                            (        1        )                where al and τl are the complex amplitude and delay of the l-th multipath, respectively, L is the number of multipaths, and p(t) is the waveform of the CIR when L=1. Herein the term “composite CIR” refers to the CIR h(t) in its entirety, as opposed to its multipath decomposition on the right hand side of Equation (1). G-rake uses the multipath decomposition to compute the noise covariance matrix that is needed in computing the optimum weights for combining the finger outputs. The multipath decomposition requires estimation of the complex amplitude and delay of each multipath, and thus is susceptible to channel estimation noise, especially when the multipaths are closely spaced. As a result, in real-world scenarios G-rake loses much of its promised performance gains that are predicted under the perfect knowledge of the channel. Details of the realistic G-rake performance can be found in, for example, G. Kutz and A. Chass, “On the Performance of a Practical Downlink CDMA Generalized Rake Receiver”, Proceedings of IEEE Vehicular Technology Conference, pp. 1352-1356, September 2002, incorporated by reference herein.            2. Efficient and effective finger assignment algorithms have yet to be developed for a G-rake receiver. The performance of interference suppression depends strongly on the locations of additional fingers. The search for optimum locations of additional fingers, however, is computationally prohibitive. For example, each search step requires inversion of the noise covariance matrix. U.S. patent application Ser. No. 09/845,950 to Y.-P. E. Wang, G. E. Bottomley and K. Urabe, discloses an iterative method in lieu of matrix inversion. The iterative method, however, is not guaranteed to converge. The solution given by a diverging iteration can severely degrade the receiver performance. The article of Y.-P. E. Wang, J.-F. Cheng and E. Englund, cited heretofore, discloses another finger assignment strategy that simply puts two additional fingers one chip before and after the known CIR. A heuristic search algorithm was proposed in the article of G. Kutz and A. Chass, cited heretofore, proposes a heuristic search algorithm (“Kutz and Chass scheme”). These finger assignment schemes, while simple, are not optimum, and thus can be ineffective in interference suppression, especially when the multipaths are closely spaced and the channel is severely dispersive.        3. Other disadvantages of a conventional rake receiver, such as the need for finger tracking and high sample rate, still exist in a G-rake receiver.LMMSE Receiver        
A linear-minimum-mean-square-error (LMMSE) receiver is typically designed based upon the composite CIR. A conventional LMMSE receiver has uniformly spaced taps, and the tap coefficients can be computed based on the composite CIR to minimize the mean output error energy. An LMMSE receiver is thus robust in the presence of the channel estimation errors. For details, see A. Mirbagheri and Y. C. Yoon, “A Linear MMSE Receiver for Multipath Asynchronous Random-CDMA with Chip Pulse Shaping”, IEEE Transactions on Vehicular Technology, vol. 31, no. 5, pp. 1072-1086, September 2002.
A conventional LMMSE receiver has following disadvantages:                1. The number of uniformly spaced taps is much more than the number of taps (fingers) in a rake receiver, thus having more complexity.        2. To improve the performance, an LMMSE receiver will have fractionally-spaced taps, meaning more than one tap per chip. This further increases the complexity, and may be numerically unstable when the number of taps is large.        3. To obtain the optimum tap coefficients requires inversion of the noise covariance matrix. The dimension of the covariance matrix is the same as the number of taps, so this becomes comes impractical for large number of taps.        4. To avoid matrix inversion, an LMMSE receiver can be made to adapt to changes in CIR. The amount of computations in adaptive algorithms is often too huge to be practical. Adaptive algorithms also cause loss in performance.        